The Internet of Vehicles (IoV) refers to the integration of vehicles with internet connectivity and communication technologies, enabling them to communicate with each other, with infrastructure, and with other entities in the environment. Mobile networks, the automobile industry, and communication technology have all advanced to the point where cars are now more than simply basic means of transportation. Smart equipment in cars, such radar, GPS antennae, onboard computers, wireless sensors, and so forth, can process and gather vast amounts of data while facilitating inter-vehicle communication. The period of traditional transportation services is giving way to an intelligent era of automotive growth. The application of Artificial Intelligence (AI) in IoV has the potential to revolutionize the automotive industry and transportation systems. Some scopes of AI-based technologies in the IoV are Connected Vehicles, Autonomous Vehicles, Traffic Management, Enhanced Safety and Security, In-Vehicle Entertainment and Personalization, Big Data Analytics, Environmental Impact, etc. This paper aims to provide theoretical foundations and conduct a critical review for Machine Learning (ML), AI and the leading models and algorithms to resolve IoV applications’ challenges.